Machine Learning Engineer
London
InstaDeep
InstaDeep delivers AI-powered decision-making systems for the Enterprise. With expertise in both machine intelligence research and concrete business deployments, we provide a competitive advantage to our customers in an AI-first world.Join us to be a part of the AI revolution!
About DeepPCB:DeepPCB is InstaDeep’s AI-powered Place & Route PCB (Printed Circuit Board) design tool. We use a combination of deep reinforcement learning and high-performance computing to automate and scale PCB place-and-route workflows, accelerating hardware innovation globally.Learn more at deeppcb.ai.
Role Overview:We are looking for a Machine Learning Engineer to join the DeepPCB team and help push the boundaries of AI for electronic design automation (EDA). You will develop, optimize, and deploy cutting-edge machine learning and reinforcement learning models focused on automating complex PCB design problems, working closely with researchers and engineers to bring ideas to life.
Responsibilities:
- Develop scalable and efficient machine learning algorithms to tackle PCB place-and-route challenges.
- Adapt and optimize ML models for large-scale distributed computing environments (e.g., GPUs, multi-node clusters).
- Build, test, and deploy robust production-level ML systems integrated into the DeepPCB platform.
- Collaborate with research scientists, software engineers, product managers, and business development teams.
- Clearly document and present your work internally and externally, adjusting technical depth based on the audience.
- Participate in technical discussions, design reviews, and customer-facing activities when required.
Requirements:
- B.Sc., M.Sc., or Ph.D. in Computer Science, Machine Learning, Electrical Engineering, or a related technical field.
- 2–5 years of professional experience in applied machine learning or engineering roles.
- Strong expertise in Machine Learning and Deep Learning, with exposure to Reinforcement Learning as a plus.
- Proficiency in Python and modern ML libraries (e.g., TensorFlow, PyTorch, JAX, or Keras).
- Experience with version control systems (GitHub, GitLab) and knowledge of clean, maintainable coding practices.
- Familiarity with CI/CD pipelines for automating ML workflows.
- Ability to thrive in a fast-paced, collaborative, and dynamic environment.
Nice to haves:
- Prior experience with PCB design, EDA tools, or related optimization problems.
- Hands-on experience in high-performance computing environments (e.g., Kubernetes, Ray, Dask).
- Contributions to open-source projects, publications, or top placements in ML competitions (e.g., Kaggle).
- Expertise in related fields such as Computer Vision, Representation Learning, or Simulation Environments.
Right to work: Please note that you will require the legal right to work in the location you are applying for.
* Salary range is an estimate based on our AI, ML, Data Science Salary Index 💰
Tags: CI/CD Computer Science Computer Vision Deep Learning EDA Engineering GCP GitHub GitLab Google Cloud JAX Keras Kubernetes Machine Learning ML models Open Source Pipelines Python PyTorch Reinforcement Learning Research TensorFlow
Perks/benefits: Career development
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